Method and apparatus for left ventricular end diastolic pressure measurement

ABSTRACT

A non-invasive and convenient method and apparatus for approximation of left ventricular end diastolic pressure (LVEDP) can be used in both hospital/clinic environments and nursing home or home environments. The method and apparatus use non-invasive sensors and a new “cardiac triangle” computational method to obtain an approximation of LVEDP. The computational method uses hemodynamic and electrocardiogram (ECG) waveforms as input, which can be collected by a portable device or devices.

PRIORITY CLAIM

The present application is a continuation of International PatentApplication No. PCT/US19/14378, filed Jan. 18, 2019, which claimspriority to U.S. Provisional Patent Application No. 62/623,095, filedJan. 29, 2018, and U.S. Provisional Patent Application No. 62/618,988,filed Jan. 18, 2018, all of which are incorporated herein in theirentireties by reference.

FIELD

The present application relates to methods and apparatus for measurementof left ventricular end diastolic pressure (LVEDP).

BACKGROUND

Heart failure (HF) is a condition in which the heart fails to pumpenough blood to meet the body's metabolic demands. Current estimateshows that approximately 5.7M adults suffer from HF in United States,and this number is expected to increase to 8M within the next 15 years.

Left ventricular end diastolic pressure (LVEDP) is an important measureof left ventricle function. Elevated LVEDP is generally indicative ofpoor left ventricular (LV) function in patients experiencing heartfailure with preserved ejection fraction (HFpEF) or heart failure withreduced ejection fraction (HFrEF). Therefore, LVEDP is a useful index inmanagement of HF and evaluating the risk of cardiac complications aftermyocardial infarction (AMI).

Direct measurement of LVEDP includes a highly invasive procedure when itis measured during routine angiography catheterization in CathLab.Indirect evaluation of LVEDP that is being used in critical care unitsis based pulmonary capillary wedge pressure (PCWP) or pulmonary arterydiastolic pressure (PADP) measurement utilizing inflated ballooncatheters. These indirect methods are invasive and can only be used inhospital environment. Additionally, these indirect methods areinaccurate in disease conditions such as mitral valve disease andpulmonary vascular diseases. For example, indirect methods overestimateLVEDP in mitral stenosis.

Efforts have been made to approximate LVEDP noninvasively. Most of thesemethods are based on bulky imaging modalities such Echocardiogram. Otherinvestigators have introduced non-invasive methods of approximatingLVEDP without imaging modalities. However, these methods are eitherhybrid (need some invasive measurement) or they require simultaneousarterial pressure and expiratory pressure during Valsalva maneuver.Therefore, current methods for non-invasive approximation of LVEDP, likeinvasive measurements of LVEDP, can only be employed in a hospitals orclinic environments.

It would be desirable, therefore, to develop new methods and other newtechnologies for non-invasive approximation of LVEDP, that overcomesthese and other limitations of the prior art.

SUMMARY

This summary and the following detailed description should beinterpreted as complementary parts of an integrated disclosure, whichparts may include redundant subject matter and/or supplemental subjectmatter. An omission in either section does not indicate priority orrelative importance of any element described in the integratedapplication. Differences between the sections may include supplementaldisclosures of alternative embodiments, additional details, oralternative descriptions of identical embodiments using differentterminology, as should be apparent from the respective disclosures.

In present disclosure describes a novel non-invasive and easy-to-usemethod and apparatus for approximation of LVEDP that can be used in bothhospital/clinic environment and at nursing home or home environment. Themethod and apparatus do not need any physiologic or pharmacologicmaneuvers such as the Valsalva maneuver. Instead, the method is based ona non-invasive arterial waveform measurement and electrocardiogram(ECG), both of which can be done by a simple portable device or devices.The method can also be done as a part of a routine cardiac Millprocedure. IN addition, the methods as described herein may be adaptedfor semi-invasive and beat-to-beat evaluation of LVEDP with inlineradial cath pressure measurement in hospital or clinic environments.

In an aspect of the disclosure, method for approximation of leftventricular end diastolic pressure (LVEDP) using non-invasive sensorscoupled to a computing apparatus may include receiving, by at least oneprocessor of the computing apparatus, hemodynamic waveform data from anon-invasive sensor coupled to a patient. The method may further includereceiving, by the at least one processor, electrocardiogram (ECG) dataor heart sound waveform data from a second non-invasive sensor coupledto the patient. The method may further include determining, by the atleast one processor, at least one of a pre-ejection period (PEP) or anisovolumic contraction time (ICT), based on simultaneous portions of thehemodynamic waveform data and at least one of the ECG data or the heartsound waveform data. The method may further include calculating, by theat least one processor, an LVEDP based on the intrinsic frequencies andat least one of the PEP and the ICT. The method may further includeencoding the LVEDP as digital data for at least one of storage,transmission, or human-comprehensible output.

In some embodiments, the method may further include calculating, by theat least one processor, a contractility feature, for example intrinsicfrequencies or a derivative of a waveform, based on the hemodynamicwaveform data. In related, alternative aspects of the method, the atleast one processor may calculate the LVEDP as a function of thecontractility feature and the PEP; as a function of the contractilityfeature, the PEP, and a cuff blood pressure (DBP); as a function of thecontractility feature and the ICT; as a function of the contractilityfeature, the ICT, and a cuff blood pressure (DBP); as a function of thecontractility feature, the PEP, and the ICT; and/or as a function of thecontractility feature, the PEP, the ICT, and a cuff blood pressure(DBP).

In some embodiments, the method may include collecting a heart soundwaveform. In such cases, the method may further include correcting thecalculating of the LVEDP for valvular diseases based on the heart soundwaveform.

In some embodiments, the method may include determining a pulse wavevelocity from the hemodynamic waveform data. The method may furtherinclude calculating the at least one of the PEP and the ICT using thepulse wave velocity to improve accuracy.

In an aspect of the method, calculating the intrinsic frequencies may bebased on at least one of: carotid pressure waveform, aortic wallwaveform, carotid vessel wall waveform, radial pressure waveform, radialvessel wall waveform, brachial pressure waveform, brachial vessel wallwaveform, femoral pressure waveform, femoral vessel wall waveform, orpulsOx waveform. Calculating the intrinsic frequencies may be based onat least one of: calculating a surrogate from non-invasively measuredejection fraction (EF) and fractional shortening (FS). Calculating theintrinsic frequencies is based on at least one of a flow or velocitywaveform.

As used herein, a “client device” or LVEDP apparatus includes at least acomputer processor coupled to a memory and to one or more ports,including at least one input port and at least one output port (e.g., adesktop computer, laptop computer, tablet computer, smartphone, PDA,etc.). A computer processor may include, for example, a microprocessor,microcontroller, system on a chip, or other processing circuit. As usedherein, a “processor” means a computer processor. An LVEDP apparatus orclient device includes a memory coupled to at least one processor, thememory holding instructions that when executed by the processor causethe apparatus or client device to perform operations of the methodsdescribed herein. An LVEDP apparatus or client device may furtherinclude non-invasive sensors for capturing a patient's hemodynamic, ECG,and/or heart sound waveforms.

To the accomplishment of the foregoing and related ends, one or moreexamples comprise the features hereinafter fully described andparticularly pointed out in the claims. The following description andthe annexed drawings set forth in detail certain illustrative aspectsand are indicative of but a few of the various ways in which theprinciples of the examples may be employed. Other advantages and novelfeatures will become apparent from the following detailed descriptionwhen considered in conjunction with the drawings and the disclosedexamples, which encompass all such aspects and their equivalents.

BRIEF DESCRIPTION OF THE DRAWINGS

The features, nature, and advantages of the present disclosure willbecome more apparent from the detailed description set forth below whentaken in conjunction with the drawings in which like referencecharacters identify like elements correspondingly throughout thespecification and drawings.

FIG. 1 is a chart illustrating fundamental properties of hemodynamicwaveforms as known in the art.

FIG. 2A is a detail of the chart shown in FIG. 1, illustratingrelationships between fundamental properties as a “cardiac triangle.”

FIG. 2B-2E are graphs showing further relationships and aspects of thecardiac triangle and related method.

FIG. 3 is a flow chart illustrating aspect of LVEDP approximation for apatient.

FIG. 4 is a block diagram illustrating an apparatus for non-invasiveapproximation of LVEDP.

FIG. 5 is a flow diagram illustrating aspects of a method fornon-invasive approximation of LVEDP for use by an apparatus as shown inFIG. 4 or 10.

FIGS. 6-9 are flow charts illustrating additional aspects for use withthe method of FIG. 5.

FIG. 10 is a conceptual block diagram illustrating components of anapparatus or system for non-invasive approximation of LVEDP.

FIG. 11 is a flow diagram illustrating aspects of an alternative methodfor non-invasive approximation of LVEDP for use by an apparatus as shownin FIG. 4 or 10.

FIGS. 12A-B are flow charts illustrating additional aspects for use withthe method of FIG. 11.

FIG. 13 is a conceptual block diagram illustrating components of anapparatus or system for non-invasive approximation of LVEDP using themethod of FIG. 11.

FIG. 14 is a chart illustrating approximation of LVEDP from AoDP, EF,PEP, and LV ejection time.

FIG. 15 is a chart illustrating approximation of LVEDP from linearregression using EF, PEP, and ejection time.

FIG. 16 is a chart illustrating approximation of LVEDP from multipleregression (interaction model) using EF, PEP, and ejection time.

FIG. 17 is a chart illustrating Correlation between LVEDP and Equation(9).

DETAILED DESCRIPTION

Various aspects are now described with reference to the drawings. In thefollowing description, for purposes of explanation, numerous specificdetails are set forth in order to provide a thorough understanding ofone or more aspects. It may be evident, however, that the variousaspects may be practiced without these specific details. In otherinstances, well-known structures and devices are shown in block diagramform in order to facilitate describing these aspects.

Operation of the apparatus and methods described herein may be betterunderstood in view of fundamentals of cardiac measurement parameters.Intrinsic frequency (IF) method is a new method for analysis of coupleddynamical systems described by the inventors hereof. In its simplestform a coupled dynamical system is composed of two systems. Aphysiological example of a coupled dynamical system is leftventricle-aortic system. The IF method reveals clinically usefulinformation when applied to arterial pressure waveform (the output ofLV-Aortic system). The intrinsic frequencies of systemic pressure wavesare called cardiovascular intrinsic frequencies denoted by ω₁ and ω₂. ω₁is the intrinsic frequency of the LV mostly dominated by the dynamics ofthe LV and ω₂ is the intrinsic frequency of the aortic system that ismostly dependent on the dynamics of the aorta and vascular network.

Our previous studies (unpublished) have shown that on is mainlydetermined by the LV contractility (Ctr) while ω₂ is mostly determinedby the arterial wave dynamics and afterload. In addition, the differencebetween on and ω₂ (ω₁−ω₂) can be a measure of LV-arterial coupling(LVAC).

Pre-ejection period (PEP) is one the systolic time interval (STI)parameters that is mainly dependent on the dynamics of the heart. Paststudies showed that PEP is influenced by LV contractility (Ctr), leftventricle end diastolic pressure (LVEDP), and afterload (AL).

Although STI method is an obsolete method of practice in cardiology andhas been abandoned since early 80s, one of its parameters, PEP, can addconsiderable value to IF method. Mathematically, PEP is orthogonal to ω₁and ω₂, and other IF dimensions. This means that PEP providesinformation that cannot be retrieved from IF five-dimensional (5D)space. One of the critically important parameters that can be computedby the combination of PEP and IFs is LVEDP.

FIG. 1, adopted from Lewis, Richard P., et al. Circulation 56.2 (1977):146-158.), shows a graph 100 of arterial (aortic) pressure waveform 102,left ventricular (LV) pressure 104, ECG 106, and pre-ejection period(PEP) 108 during a cardiac cycle. All the illustrated parameters may bemeasured non-invasively using new or prior art methods.

The measurement parameters of a cardiac shown in graph 100 can be usedto compute LVEDP using a “cardiac triangle,” so called because of atriangular relation between involved parameters. FIG. 2 illustratescomputation of LVEDP using a cardiac triangle in the PEP 108 shown inFIG. 1, as an example, wherein AoDP is the aortic diastolic pressure,LVEDP is the value of the LV end diastolic pressure, and “Ctr” is the LVcontractility. A triangle 202 is defined by the width of the PEP 108 asone side and the difference between LVEDP and AoDP as the other side.The slope of the hypotenuse of the cardiac triangle is a function(tan⁻¹) of LV contractility. The AoDP is the aortic diastolic pressurethat is dependent on the systemic vascular tone and LV-arterialcoupling. LVEDP may be computed from the Cardiac Triangle, as follows.

Using FIG. 2, the slope of the contractility function Ctr can be writtenas:

$\begin{matrix}{{Ctr} = \frac{{AoDP} - {LVEDP}}{PEP}} & (1)\end{matrix}$

Solve for LVEDP gives:

LVEDP=AoDP−Ctr×PEP  (2.0)

In a more general form:

LVEDP=α₀+α₁AoDP+α₂ Ctr×PEP  (3.0)

Where, α_(i) can be universal physiological constant or a patientspecific constant.

In a simplest form AoDP can be approximated by a brachial cuff pressureor any other noninvasive techniques for diastolic blood pressuremeasurement (DBP).

Ctr can be approximated using different methods, including at leastfollowing approaches:

-   -   1. The derivative of the carotid pressure waveform before the        reflected wave arrival time.    -   2. The maximum positive derivative of the carotid pressure wave        before the first local maximum.    -   3. The ratio of maximum positive derivative of the carotid        pressure waveform divided by the slope of the descending part of        the carotid pressure waveform after the dicrotic notch or as it        described by Newlin et al (Newlin D B, Levenson R W (1979)        Pre-ejection Period: Measuring Beta-adrenergic Influences Upon        the Heart. Psychophysiology 16: 546-552).    -   4. The maximum positive derivative of the carotid pressure wave        before the first local maximum to the pulse pressure (pulse        pressure=arterial systolic pressure−arterial diastolic        pressure).    -   5. The ratio of the derivative of the carotid pressure waveform        before the reflected wave arrival time to the pulse pressure.    -   6. The ratio of the derivative of the carotid pressure waveform        before the reflected wave arrival time to the pulse pressure.    -   7. As an alternative to carotid pressure waveform in 1-6, aortic        wall waveform, carotid vessel wall waveform, radial pressure        waveform, radial vessel wall waveform, brachial pressure        waveform, brachial vessel wall waveform, femoral pressure        waveform, femoral vessel wall waveform, or pulseOx waveform can        be used.    -   8. As a different approach the maximum slope before the peak of        aortic, carotid, or other large vessels flow waveform can be        used to approximate Ctr.

Noninvasively measured ejection fraction (EF) and fractional shortening(FS) from echo, CTSacn or MRI can be used as a surrogate of Ctr.

In a general form, AoDP can be replaced with afterload (AL) andLV-arterial coupling (LVAC). Also, the slope can be written as afunction of Ctr. More generally:

LVEDP=K ₁(Ctr,LVAC,AL,PEP)  (4.0)

Another way of computing LVEDP from Cardiac Triangle is to useisovolumic contraction time (ICT). In this case the, Equation 4.0 and5.0 can be written as:

LVEDP=K ₂(Ctr,LVAC,AL,ICT)  (5.0)

Combination of both ICT and PEP may also be sued to increase theaccuracy of the LVEDP approximation:

LVEDP=K ₃(Ctr,LVAC,AL,ICT,PEP)  (6.0)

In cases of valvular diseases such as mitral valve and aortic valvediseases, the sound wave can be used to correct for Equations 2.0through 6.0. The contractility index in Equations 2.0 through 6.0 can bemeasured from carotid waveform, radial waveform, femoral waveform orpulseOx waveform. Depending on the location waveform measurement thefunctions (K1−K3) may be different. All of the parameters in Equations2.0, 3.0 and 4.0 can be measured non-invasively using portable devices.Waveforms measured using non-invasive methods may sometimes be referredto herein as “non-invasive waveforms.”

In some embodiments, the computation may make use of intrinsic frequency(IF) parameters as a special case of Ctr, as described in more detailherein below. The IF parameters ω₁ and ω₂ may be computed fromnon-invasively collected hemodynamic waveforms as described in U.S. Pat.No. 9,026,193 by inventors hereof (the '193 patent), which isincorporated by reference herein. For example, ω₁ and ω₂ may be computedusing the Sparse Time-Frequency Representation (STFR) method, usingEquation 2 in the '193 patent.

AL, LVAC, and Ctr are related to intrinsic frequency parameters ω₁ andω₂, as follows:

$\begin{matrix}{{f_{1}({IFs})} = \frac{{f_{2}({IFs})} - {LVEDP}}{PEP}} & (2.1)\end{matrix}$

Solving Equation 2.1 for LVEDP results in:

LVEDP=f ₂(IFs)−PEP×f ₁(IFs)  (3.1)

More generally:

LVEDP=K ₁(IFs,PEP)  (4.1)

Thus, LVEDP can be computed from IF parameters and PEP, all of which canbe collected non-invasively.

In an aspect, since brachial diastolic pressure is almost the same asAoDP, including cuff blood pressure (DBP) may increase the accuracy ofthe Equation 4.1:

LVEDP=K ₂(IFs,PEP,DBP)  (5.1)

Another way of computing LVEDP from IF and STI parameters may includeusing isovolumic contraction time (ICT). In this case the, Equations 4.1and 5.1 can be written as:

LVEDP=K ₃(IFs,ICT)  Eq. 6.1

In an alternative, DBP can also be included with ICT:

LVEDP=K ₄(IFs,ICT,DBP)  Eq. 7.1

Combination of both ICT and PEP with the IFs may increase the accuracyof the LVEDP approximation, as follows:

LVEDP=K ₅(IFs,ICT,PEP)  Eq. 8.1

Once again, DBP can be included:

LVEDP=K ₆(IFs,ICT,PEP,DBP)  Eq. 9.1

In cases of valvular diseases such as mitral valve and aortic valvediseases, the sound wave can be used to correct for Equations 4.0-6.0 or4.1-9.1. Advantages of approximating LVEDP using any of the methodsdescribed above include the ease of obtaining all the required inputnon-invasively, for example using portable devices.

The contractility feature (e.g., intrinsic frequencies or derivative) inEquations 4.1 through 9.1 can be obtained from measurements of carotidwaveform, radial waveform, femoral waveform or pulse ox waveform.Depending on the location of measurement, the functions (K1-K6) may bedifferent. In some embodiments, AoDP can be approximated by a brachialcuff pressure or any other noninvasive techniques for diastolic bloodpressure measurement (DBP).

Intrinsic frequency is useful for revealing clinically relevantinformation about the dynamics of the left ventricle (LV), arterialsystem and their interactions. IF frequencies are operating frequenciesbased on the Sparse Time-Frequency Representation (STFR), treating theLV combined with the aorta and the remaining peripheral arteries as acoupled dynamical system (heart+aortic tree) which is decoupled uponclosure of the aortic valve. Utilizing the IF method, a processor canextract two IF frequencies, ω1 and ω2 (along with other independentvariables), from a single arterial blood pressure waveform. Oneimportant advantage of the IF method is that the absolute magnitude ofthe arterial pressure wave is not required to extract the IF parameters,only the waveform morphology (sometimes referred to herein as “waveformfeatures”). As such, the IFs can be easily acquired noninvasively,instantaneously, and inexpensively using a smartphone or arterialapplanation tonometry. The first IF, ω1, describes the dynamics of thesystolic phase of the cardiac cycle where the LV and aorta (vasculature)are a coupled dynamic system. The second IF, ω2, is dominated by thedynamics of the vasculature.

Previous studies have indicated that ω1 is mainly determined by the LVcontractility while ω2 is mostly determined by vascular function (e.g.arterial stiffness, arterial wave dynamics, and afterload). In a blindclinical study, it was shown LV ejection fraction (LVEF, a surrogate ofLV contractility) derived using IF applied to carotid waveformsextracted using an iPhone, were similar to those measured from cardiacmagnetic resonance imaging (CMRI) (r=0.74, P<0.00001). Importantly, avery strong correlation between LVEF measured by CMRI and LVEF computedby IF (LVEF-IF) was observed (r=0.94, p<0.0001) among HF patients. Ithas been demonstrated that detection of cardiac systolic dysfunction (asmeasured by LVEF) via the noninvasive LVEF-IF method was more accurateand sensitive than 2D echocardiography. In addition, central arterialstiffness (carotid-femoral pulse wave velocity (PWV)) can be computedusing IF of a single noninvasively measured carotid pressure waveform(without any need for ECG measurement and/or femoral tonometry).Estimated PWV by IF method is equivalent to PWV measurements obtained bydirect methods in predicting the risk for CVD. The IF method is apowerful tool for noninvasive ventricular performance (contractility)and vascular function (afterload) evaluation.

The present disclosure includes a discussion of a new systems-basedapproach, called Cardiac Triangle Mapping (CTM), for hemodynamicevaluation of the LV. This method uses pre-ejection period (PEP) and IFmathematics to compute LVEDP. Other, more general approaches withoutusing IFs for approximation of LVEDP are also described.

The intrinsic frequency (IF) method models a dynamic system as an objectrotating around an origin. The angular velocity of the rotation is theintrinsic frequency. In the coupled LV-aorta system, the average angularvelocity of rotation (instantaneous frequency) during systole when LVand aorta are couple together is ω1. The average angular velocity duringdiastole when aorta gets decoupled from LV (after the closure of theaortic valve) is ω2. Simply put, the IF method assumes that theinstantaneous frequency of a coupled dynamical system is piecewiseconstant in time with the step that occurs at the time of decoupling. Inthe LV-aorta system, the decoupling time is the time of the closure ofthe aortic valve. From the definition, IF frequencies are fundamentallydifferent than Fourier harmonics or any other resonance-typefrequencies. The mathematical formulation of IF method is as follows:

Minimize:∥p(t)−χ(0,T ₀)[(a ₁ cos(ω₁ t)+b ₁ sin(ω₁ t)]−χ(T ₀ ,T)[(a ₂cos(ω₂ t)+b ₂ sin(ω₂ t)]−c∥ ₂ ²  (9.2)

This L2 minimization is subject to continuity at T0 (time of thedecoupling=time of the dicrotic notch) and periodicity of the waveform.Here, χ(a,b) is the indicator function (χ(a,b)=1 if a≤t≤b and χ(a,b)=0otherwise) and p(t) is the arterial waveform. a1, a2, c, b1, b2, ω1, andω2 are the unknowns that can be found by solving this nonconvexminimization problem.

Referring to FIG. 3, aspects of a method 300 for applying the foregoingcomputational process for diagnosis and therapy summarizes use of theapparatus and computer-implemented methods described in more detailbelow. Except for the operations 318, 320, any one or more of thediagrammed operations of the method 300 may be performed automaticallyusing an LVEDP measurement apparatus as described herein.

The IF method uses the information stored in an arterial waveform (e.g.carotid waveform) and creates a multidimensional IF space. Thesedimensions include the ω1 and ω2, duration of the cycle and thecoordinates of the decoupling point. The decoupling coordinates arerepresented as relative height of decoupling at the dicrotic notch(RHDN) and time of decoupling at the dicrotic notch (T0). Previousstudies have indicated that LVEF (surrogate of LV contractility),LV-arterial coupling optimality, and central pulse wave velocity (amajor determinant of arterial impedance and pulsatile afterload) can beevaluated as function of IF parameters (FIG. 2B). Previous resultsindicate that LV contractility and afterload can be approximated as afunction of IFs (ω1, ω2, . . . ). Therefore, without loss of generality,we can represent LV contractility and afterload as functions of ω1 andω2.

Ctr≈f ₁(ω₁,ω₂),  (9.3)

Ctr≈f ₂(ω₁,ω₂),  (9.4)

Referring chart series 210 of FIG. 2B, IF creates a 5-dimensional IFspace from a pressure waveform, with ω1, ω2, T0, RHDN (verticaldouble-headed arrow divided by the total range), and T as thedimensions. The representative value in IF space can then be mapped tophysiological space where LVEF (a surrogate for Ctr) and central pulsewave velocity (PWV) can be computed.

Systolic time interval (STI) method was first introduced in the 1960s.Clinical studies have shown that LV function performances such ascontractility and preload can be approximated under certain conditionsusing STI methods. Two major components of the STI method are LVejection time (LVET) and pre-ejection period (PEP). LVET is the timeinterval from the opening of the aortic valve to the closure of theaortic valve marked by the dicrotic notch (note that LVET is the same asT0 in the IF method). PEP is the time interval from the beginning of theQRS complex to the opening of the aortic valve. QRS complex is acombination of Q wave, R wave, and S wave from ECG where Q wave is anydownward deflection immediately after the P wave, R wave is an upwarddeflection after Q wave, and the S wave is a rapid downward deflectionafter the R wave. Previous studies have shown that LV preload isinversely proportional to PEP at a given LV contractility and afterload.Chart 220 of FIG. 2C shows how PEP is measured from simultaneouspressure waveform and electrocardiogram (ECG). Two major systolic timeinterval components, pre-ejection period (PEP) and LV ejection time(LVET) are shown. PEP is the time interval from the beginning of the QRScomplex to the opening of the aortic valve. LVET is the time intervalfrom the opening of the aortic valve to the closure of the aortic valvemarked by the dicrotic notch. The upper waveform is the aortic pressurewaveform (AoP) and the lower waveform is the ECG waveform.

Further, more detailed aspects of the cardiac triangle method arediscussed in connection with FIGS. 2D—below. Cardiac Triangle Mapping(CTM) is based on the fact that ventricular function is modulated bythree factors: (i) the contractile state of the myocardium orcontractility, (ii) the afterload that is related to vascular functionand LV-arterial coupling, and (iii) the preload, which can be quantifiedby LVEDP.

IF parameters such as ω1 and ω2 are extracted from the arterialwaveforms. These waveforms are the result of interactions between LVcontractility and vascular function (resistance, compliance, LV-aortacoupling); therefore, they carry little or no information about thestate of the LV preload. This means that PEP provides information thatcannot be retrieved from IFs (ω₁ and ω₂). At a fixed LV contractilityand afterload, PEP changes (inversely) as preload change. Since PEP isrelated to LV preload while ω₁ and ω₂ are not, PEP should be orthogonal(or at very least not parallel) to ω₁ and ω₂ (and other IF dimensions).As a result, a combination of IFs (ω₁ and ω₂) and PEP creates a completeset that can map LV dynamics, and subsequently provide information aboutthe hemodynamics of LV. The CTM hypothesis states that ω₁ and ω₂, PEPmap the global ventricular function. All LV-related mechanicalbiomarkers such as LVEDP can be computed as a function of IFs (e.g. ω₁,ω₂) and PEP. Mathematical expressions are provided in Eqs. 2.1-9.1above.

The state of LV performance is defined by Ctr, AL, and preload;therefore, it can geometrically be represented as a triangle (ΔABC inFIG. 2D). For the purposes of this manuscript, we will refer to it ascardiac triangle. Inspired by the shape of the pressure and ECGwaveforms in a cardiac cycle (FIG. 2D), and without loss of generality,we assume the cardiac triangle is a right triangle where PEP is one leg(AC), afterload minus LVEDP is the other leg (BC), and the slope of theAB line is Ctr (in other words, the tangent inverse of Ctr is the angle<A). This choice of Ctr is in agreement with past studies that showed LVdp/dtmax is a measure of contractility (FIG. 2D). In our assumption, thenonlinear curves from point A to point B and A to C are approximated asstraight lines. The error associated with assuming AB and AC as straightlines can be reduced by appropriate usage of nonlinear parameters suchas According to the triangle of FIG. 2D, the relationship of Eq. 1derives. The graph 230 of FIG. 2D show the cardiac tringle shapeinspired by the shape of LV pressure, aortic pressure, and ECG waveform.Uppermost waveform in the graph is LV pressure, slightly underneath itin the graph is aortic pressure, and lowest waveform in the graph isECG. ECG was scaled and adjusted for better visualization.

Physiological or physical parameters such as LV contractility, arterialdiastolic pressure, LVEDP, etc. are the edges, angles, or vertices ofthe cardiac triangle (FIG. 2E). As described in the previous paragraph,the edges are not necessarily straight. The edges can be curvilinear asshown in graph 240, FIG. 2E. A triangle formed by ω1, ω2, and PEP (the“IF-triangle”) can also define the full state of LV performance henceallowing for computation of LVEDP. This is based on a simple law ofgeometry: by knowing three components (e.g. three sides or two sides+oneangle), the whole triangle can be solved. Without loss of generality,IF-triangle can be considered as a triangle with straight sides as shownin graph 250 since IF parameters (e.g. ω1 and ω2) carry non-linearitiesassociated with the LV-aorta system. FIG. 2E shows a schematic 240 of ageneralized cardiac triangle mapping (CTM), at 250 shows a simplifiedIF-based CTM with straight edges. Ctr is LV contractility and tan−1 istangent inverse. Derivation of a solution for LVEDP in view of thecardiac triangle is given above (Eqs. 2.1-4.1). An explicit version ofEq. 4.1 is given below:

LVEDP=f ₂(ω₁,ω₂)−f ₁(ω₁,ω₂)×PEP  (9.5)

Data indicates that ω₁ corrected with the LV ejection time (ω₁√{squareroot over (T_(o))}, where T_(o) is the LVET) is strongly correlated withLVEF. Therefore, by introducing a minor error, we can replace f₁ (orCtr) in equation 9.5 with LVEF/√{square root over (T_(o))}. Aorticdiastolic pressure (AoDP) may also be a surrogate for AL). Hence,Equation 9.5 is simplified to:

$\begin{matrix}{{LVEDP} = {{c_{1}{AoDP}} - {c_{2}\frac{{LVEF} \times {PEP}}{\sqrt{T_{o}}}}}} & (9.6)\end{matrix}$

Here, c1 is a unitless constant and c2 is a constant with a unit ofmmHg/√{square root over (second)}. Linear multiple regression may beused to compute the best value for c1 and c2.

Referring to FIG. 3, aspects of a method 300 for applying the foregoingcomputational process for diagnosis and therapy summarizes use of theapparatus and computer-implemented methods described in more detailbelow. Except for the operations 318, 320, any one or more of thediagrammed operations of the method 300 may be performed automaticallyusing an LVEDP measurement apparatus as described herein.

At 302, the operator determines whether the patient is diagnosed with orhas symptoms of a valvular disease, for example, mitral valve and aorticvalve diseases. If so, at 308, the operator may collect a heart soundwaveform, for example, by using a digital stethoscope.

Whether or not valvular disease is indicated, at 304, an operatorcaptures at least one hemodynamic pulse waveform from a patient usingany suitable method described below. For example, the hemodynamic pulsewaveform may be, or may include, any one or more of a carotid pressurewaveform, aortic wall waveform, carotid vessel wall waveform, radialpressure waveform, radial vessel wall waveform, brachial pressurewaveform, brachial vessel wall waveform, femoral pressure waveform,femoral vessel wall waveform, or pulse oximeter (pulsOx) waveform.Non-invasive equipment for collecting hemodynamic pulse waveform mayinclude, for example, tonometry devices that can sense pressurewaveform, microwave devices that can sense vessel wall motion, echoultrasound devices that can sense vessel wall motion, or a pulseOxdevice for obtaining a pulseOx waveform.

Likewise, at 306, the operator captures an ECG waveform, for example, byapplying an ECG device including an electrode array to the patient. Theoperations 302, 306 and 308 (if called for) are performedcontemporaneously and the resulting waveform is time-delimited sosimultaneous portions of different waveforms can be examined andanalyzed for computation of an LVEDP approximation.

At 310, the operator provides the pulse waveform to a computing devicefor computation of a contractility feature (e.g., IF or a derivative ofthe waveform). IF may be computed for example by a STFR methodreferenced herein above. In addition, at 312 the operator provides thepulse and ECG waveforms to the computing device for computation of atleast one STE parameter, PEP and/or ICT. If valvular disease isindicated, at 314 the operator may adjust parameters used to compute theLVEDP based on the heart sound waveform, for example, any parametersthat depend on the time that the PEP begins or ends.

At 316, the operator may compute LVEDP using any one of Equations4.0-6.0 or 4.1-9.1 described herein above. Optionally, at 318, theoperator may confirm the LVEDP approximated in block 316 with an LVEDPdetermined from traditional invasive procedures. Data from the invasiveprocedures may be used to calibrate sensor data for the patent so thatfuture non-invasive LVEDP determination is more accurate. At 320, theoperator considers, recommends and/or adjusts a therapeutic orpreventative plan based on the LVEDP or changes therein.

In many contexts the user will make use of a programmable deviceconfigured for performance of the technical steps and method disclosedherein. FIG. 4 shows an example of an LVEDP apparatus 400 in blockdiagram form. The apparatus 400 includes at least one processor 402coupled to a memory 404, for example, a random access memory (RAM)holding program instructions and data for rapid execution or processingby the processor during execution of methods as described herein. Whenthe apparatus 400 is powered off or in an inactive state, programinstructions and data may be stored in a long-term memory, for example,a non-volatile magnetic, optical, or electronic memory storage device,remote server, remote cloud storage or distributed ledger (not shown).Either or both of the RAM 404 or a long-term memory may comprise anon-transitory computer-readable medium holding program instructions,that when executed by the processor 402, cause the apparatus 400 toperform a method or operations as described herein. Program instructionsmay be written in any suitable high-level language, for example, C, C++,C #, or Java™, and compiled to produce machine-language code forexecution by the processor. Program instructions may be grouped intofunctional modules 408-412, to facilitate coding efficiency andcomprehensibility. It should be appreciated that such modules, even ifdiscernable as divisions or grouping in source code, are not necessarilydistinguishable as separate code blocks in machine-level coding. Codebundles directed toward a specific function may be considered tocomprise a module, regardless of whether or not machine code on thebundle can be executed independently of other machine code. In otherwords, the modules may be high-level modules only.

The LVEDP apparatus 400 may be enclosed or mounted in a housing,package, and/or circuit board 406, together with other components, forexample a user interface device 418 coupled to the processor 402 by abus 416. A user interface device may be, or may include, a touchscreen,keypad, microphone/audio transducer system, head-mounted display witheye tracking, or other device for providing information to a user andreceiving user input. Input ports 420, 422, 424 may also be coupled tothe processor 402 via the bus 416 or other coupling. Examples of inputports 420, 422, 424 include universal serial bus (USB), a Lightning™connector port by Apple™, a serial port, an audio port, wirelessreceiver, or any other useful input port or internal connection/bus forreceiving waveform data from sensors 426, 428, 430. The sensors 426,428, 430 may be housed in a separate sensor module 432, may befreestanding, independent sensor devices, or may be integrated in or onthe housing, package, and/or circuit board 406 with the processor 402and memory. In some embodiments, a portable sensor component containingat least a hydrodynamic pulse waveform sensor 426 and ECG sensor 428 arepackaged in a small package 432 that can be held against the patient'sskin over the carotid or other artery, and is coupled wirelessly (e.g.,using a Bluetooth connection) to a smartphone, notepad computer, laptopcomputer or similar portable device holding the processor 402, memory404 and user interface 418.

The hemodynamic waveform sensor 426 may be, or may include, an opticalsensor that can measure vessel wall motion, a tonometry device that canmeasure pressure waveform or movement at the skin surface, a microwavedevice that can measure vessel wall motion and ECG signals for PEPand/or ICT measurement, or an echo ultrasound device that can measurevessel wall motion. For semi-invasive and beat-to-beat evaluation ofLVEDP in hospital or clinic environments, the sensor 426 may be, or mayinclude, implanted pressure sensors in the aorta, or inline and invasiveradial or femoral catheters.

The ECG sensor 428 may be, or may include, a smartphone application andsystem with ECG ability that can be used to measure pulse waveform forIF parameters, PEP, and STI computation using an electrode array, or anECG system. A heart sound sensor 430 may be, or may include, a digitalstethoscope. Other useful sensors for providing waveform data to theprocessor 402 may be, or may include, a cuff pressure measurement devicefor DBP measurement, or a pulseOx device for pulseOX waveformmeasurement. Examples of a packaged sensor assembly 432 are provided byportable electronic hemodynamic sensor systems as described byRinderknecht, Pahlevan et, al in U.S. Pat. No. 9,026,193.

Functional modules held in the memory 404 may include, for example, acontractility feature module 408 for calculating a contractility feature(e.g., intrinsic frequencies or a derivative of the waveform) based onhemodynamic waveform data as described herein, and an STI calculationmodule 410 for calculating at least one of a PEP or ITC from ECG and/orheart sound waveform data as described herein. The memory may furtherhold a LVEDP calculation module 412 for calculating LVEDP using any oneor more of Equations 4.0-6.0 or 4.1-9.1. The memory may further hold anencoding module 414 for encoding one or more LVEDPs calculated by module412 for at least one of storage, transmittal, or output inhuman-comprehendible form by UI 418 or other user interface device. Thememory 404 may hold other functional modules as generally known in thecomputing arts for routine functionality. Other aspects of the LVEDPapparatus 400 may be as described in connection with the apparatus 1000shown in FIG. 10 or 13.

In accordance with the foregoing, and by way of additional example, FIG.5 shows aspects of a method 500 according to an embodiment forperformance by an LVEPD-estimating apparatus 400, 1000 as describedherein. Referring to FIG. 5, a computer-implemented method 500 forapproximation of left ventricular end diastolic pressure (LVEDP) usingnon-invasive sensors coupled to a computing apparatus may include, at510, receiving by at least one processor of the computing apparatushemodynamic waveform data from a non-invasive sensor coupled to apatient. The waveform data may include, for example carotid pressurewaveform. As an alternative to carotid pressure waveform, or inaddition, receiving the waveform data 510 may include receiving aorticwall waveform, carotid vessel wall waveform, radial pressure waveform,radial vessel wall waveform, brachial pressure waveform, brachial vesselwall waveform, femoral pressure waveform, femoral vessel wall waveform,or pulse oximeter (pulsOx) waveform. In some embodiments, non-invasivelymeasured ejection fraction (EF) and fractional shortening (FS) fromecho, CTSacn or MM can be used as a surrogate of IF parameters. As analternative, the contractility feature (e.g. intrinsic frequencies) offlow or velocity waveforms instead of pulse or pressure waveforms can beused in Equations 2.0-6.0 or 2.1-9.1.

In an aspect of the operation 510 relating to determination of PEP orICT, a processor of client device for providing an LVEDP output mayapproximate IF parameters can be approximated using one or more of thefollowing approaches: using simultaneously measured sound waveform atthe heart and ECG; using simultaneously measured sound waveform at thecarotid artery and ECG; using simultaneously measured sound waveform atheart and carotid waveform (Pressure, wall displacement, orflow/velocity); using simultaneously measured ECG and carotid waveform(Pressure, wall displacement, or flow/velocity); using simultaneouslymeasured ECG and aortic flow waveform (e.g. in a cardiac MRI orEchocardiogram setting); using simultaneously measured ECG and aorticwall displacement waveform; using simultaneously measured ECG andbrachial waveform (Pressure, wall displacement, or flow/velocity); usingsimultaneously measured ECG and radial waveform (Pressure, walldisplacement, or flow/velocity); using simultaneously measured ECG andfemoral waveform (Pressure, wall displacement, or flow/velocity, orusing simultaneously measured ECG and pulseOx waveform.

The method 500 may further include at 520 receiving, by the at least oneprocessor, electrocardiogram (ECG) data or heart sound waveform datafrom a second non-invasive sensor coupled to the patient. In some cases,the method includes using the heart sound waveform data to correct orconfirm an ECG waveform. The method 500 may further include at 530determining, by the at least one processor, at least one of apre-ejection period (PEP) or an isovolumic contraction time (ICT), basedon simultaneous portions of the hemodynamic waveform data and at leastone of the ECG data or the heart sound waveform data, for example asdescribed in connection with FIG. 2. The method 500 may further includeat 540 calculating, by the at least one processor, an LVEDP based on acontractility feature and at least one of the PEP and the ICT. Themethod 500 may further include at 550 encoding the LVEDP as digital datafor at least one of storage, transmission, or human-comprehensibleoutput.

Referring to FIGS. 6-9, the method 500 may include any one or moreadditional operations 600, 700, 770, 800 and 900 as described above andbelow herein. Each of these additional operations is not necessarilyperformed in every embodiment of the method, and the presence of any oneof the operations does not necessarily require that any other of theseadditional operations also be performed.

For example, referring to FIG. 6, method 500 may further include, at610, collecting a heart sound waveform, for example, using a digitalstethoscope. In some embodiments, the waveform data may be, or mayinclude, heart sounds. In such cases, the method may further include, at620, correcting the calculating of the LVEDP for valvular diseases basedon the heart sound waveform. In an alternative aspect, the method 500may include at 630, measuring, by the at least one processor, thecontractility feature by an imaging modality including at least onecardiac magnetic resonance imaging (e.g. ejection fraction or fractionalshortening) or echocardiogram (e.g. ejection fraction, fractionalshortening, or myocardial strain). The imaging modality may be used as asource of the contractility feature of the patient, in lieu of, or inaddition to, measuring the contractility feature based on thehemodynamic waveform data.

Referring to FIG. 7A, in related, alternative aspects the method 500 mayinclude, at 705, calculating, by the at least one processor, intrinsicfrequencies (as a specific cases of a contractility function) based onthe hemodynamic waveform data, for example as described in the '193Patent referenced herein. The at least one processor may calculate theLVEDP using any one or more of the Equations 4.1-9.1 For example, at 710the processor may calculate LVEDP as a function of the intrinsicfrequencies and the PEP using Equation 4.1. In an alternative, or inaddition, at 720 the processor may calculate LVEDP as a function of theintrinsic frequencies, the PEP, and a cuff blood pressure (DBP) usingEquation 5.1. In an alternative, or in addition, at 730 the processormay calculate LVEDP as a function of the intrinsic frequencies and theICT using Equation 6.1. In an alternative, or in addition, at 740 theprocessor may calculate LVEDP as a function of the intrinsicfrequencies, the ICT, and a DBP, using Equation 7.1. In an alternative,or in addition, at 750 the processor may calculate LVEDP as a functionof the intrinsic frequencies, the PEP, and the ICT, using Equation 8.1.In an alternative, or in addition, at 760 the processor may calculateLVEDP as a function of the intrinsic frequencies, the PEP, the ICT, anda DBP, using Equation 9.1. The alternative calculation methods shown inFIG. 7 may be summarized as calculating the LVEDP as a function of theintrinsic frequencies, at least one of the PEP and the ICT, andoptionally a cuff blood pressure (DBP).

FIG. 7B shows a more general expression of which the alternatives shownin FIG. 7A are a special case. At 780, the method 500 may furtherinclude calculating the contractility feature based on the hemodynamicwaveform data. The contractility feature may be, or may include,intrinsic frequencies, a derivative of the wave function, or othermeasure based on time and waveform features of the hemodynamicwaveforms. At 790, the method 500 may include, for example, the at leastone processor calculating the LVEDP as a function of the contractilityfeature, at least one of the PEP and the ICT, and optionally a DBP.

Referring to FIG. 8, in some embodiments, the method 500 may include at810 determining a pulse wave velocity from the hemodynamic waveformdata. At 820, the method may further include calculating the at leastone of the PEP and the ICT using the pulse wave velocity to improveaccuracy. Methods for calculating pulse waveform velocity are known inthe art. More accurate information regarding pulse wave velocity willenable one of ordinary skill to form a more accurate estimate of PEP orICT by correlating received waveforms with cardiac action by accountingfor differences in signal lag. This may be useful in cases where apulseOx waveform is being used. In such cases, the corresponding pulsewave velocity can be used to improve the accuracy of PEP measurement orestimation. In addition, where pulse waveforms are being captured atcarotid, radial, brachial, or femoral locations, the corresponding pulsewave velocity is likewise useful to improve the accuracy of PEPmeasurement.

Referring to FIG. 9 at 910, in an aspect of the method 500, calculatingthe contractility feature (e.g., intrinsic frequencies or derivatives ofthe waveform) may be based on at least one of: carotid pressurewaveform, aortic wall waveform, carotid vessel wall waveform, radialpressure waveform, radial vessel wall waveform, brachial pressurewaveform, brachial vessel wall waveform, femoral pressure waveform,femoral vessel wall waveform, or pulsOx waveform. In a further aspect ofthe method 500, at 920, calculating the contractility feature may bebased on at least one of: calculating a surrogate from non-invasivelymeasured ejection fraction (EF) and fractional shortening (FS). In arelated aspect of the method 500 at 930, calculating the contractilityfeature may be based on at least one of a flow or velocity waveform.

FIG. 10 is a conceptual block diagram illustrating components of anapparatus or system 1000 for approximation of left ventricular enddiastolic pressure (LVEDP) as described herein, according to oneembodiment. As depicted, the apparatus or system 1000 may includefunctional blocks that can represent functions implemented by aprocessor, software, or combination thereof (e.g., firmware).

As illustrated in FIG. 10, the apparatus or system 1000 may comprise anelectrical component 1002 for receiving hemodynamic waveform data from anon-invasive sensor coupled to a patient. The component 1002 may be, ormay include, a means for said receiving. Said means may include theprocessor 1010 coupled to the memory 1016, and to the first sensor 1014comprising a non-invasive hemodynamic sensor as described herein, theprocessor executing an algorithm based on program instructions stored inthe memory. Such algorithm may include a sequence of more detailedoperations, for example, initiating a communication session with thefirst sensor 1014, correlating a waveform from sensor 1014 with respectto a time datum, and encoding one or more characteristic features of areceived waveform from the sensor 1014 during the session in a computermemory using a numeric scheme.

The apparatus or system 1000 may further comprise an electricalcomponent 1003 for calculating a contractility feature (e.g., intrinsicfrequencies or derivative) based on the hemodynamic waveform data. Thecomponent 1003 may be, or may include, a means for said calculating.Said means may include the processor 1010 coupled to the memory 1016,the processor executing an algorithm based on program instructionsstored in the memory. Such algorithm may include a sequence of moredetailed operations, for example, calculating intrinsic frequencies asdescribed in the '193 patent, or taking a derivative of the inputwaveform.

The apparatus or system 1000 may further comprise an electricalcomponent 1004 for receiving at least one of electrocardiogram (ECG)data or heart sound waveform data from a second non-invasive sensorcoupled to the patient. The component 1004 may be, or may include, ameans for said receiving. Said means may include the processor 1010coupled to the memory 1016, and to the second sensor 1015 comprising anECG or heart sound sensor, the processor executing an algorithm based onprogram instructions stored in the memory. Such algorithm may include asequence of more detailed operations, for example, initiating acommunication session with an ECG device or digital stethoscope,correlating a waveform from the ECG device or digital stethoscope withrespect to a time datum, and encoding one or more characteristicfeatures of a received waveform in a computer memory using a numericscheme.

The apparatus or system 1000 may further comprise an electricalcomponent 1005 for determining at least one of a pre-ejection period(PEP) or an isovolumic contraction time (ICT), based on simultaneousportions of the hemodynamic waveform data and at least one of the ECGdata or the heart sound waveform data. The component 1005 may be, or mayinclude, a means for said determining. Said means may include theprocessor 1010 coupled to the memory 1016, the processor executing analgorithm based on program instructions stored in the memory. Suchalgorithm may include a sequence of more detailed operations, forexample, calculating a PEP as described in connection with FIG. 2 aboveby taking a time difference between initiation and termination of apre-ejection period from characteristic waveforms.

The apparatus or system 1000 may further comprise an electricalcomponent 1006 for calculating an LVEDP based on the contractilityfeature and at least one of the PEP and the ICT. The component 1006 maybe, or may include, a means for said calculating. Said means may includethe processor 1010 coupled to the memory 1016, the processor executingan algorithm based on program instructions stored in the memory. Suchalgorithm may include a sequence of more detailed operations, forexample, executing operations for calculation of one or more ofEquations 2.0-6.0 or 2.1-9.1 herein above.

The apparatus or system 1000 may further comprise an electricalcomponent 1007 for encoding the LVEDP as digital data for at least oneof storage, transmission, or human-comprehensible output. The component1007 may be, or may include, a means for said encoding. Said means mayinclude the processor 1010 coupled to the memory 1016, the processorexecuting an algorithm based on program instructions stored in thememory. Such algorithm may include a sequence of more detailedoperations, for example, associating a binary value representing theLVEDP with a memory location, encoding a signal for an output devicethat produces a human-comprehensible output (e.g., a video, text, audio,or other output) including a representation of the LVEDP, andassociating the encoded signal with the memory location.

The apparatus 1000 may optionally include a processor module 1010 havingat least one processor, in the case of the apparatus 1000 configured asa data processor. The processor 1010, in such case, may be in operativecommunication with the modules 1002-1007 via a bus 1012 or othercommunication coupling, for example, a network. The processor 1010 mayeffect initiation and scheduling of the processes or functions performedby electrical components 1002-1007.

In related aspects, the apparatus 1000 may include a network interfacemodule (not shown) operable for communicating with a storage device overa computer network. The first sensor 1014 may be, or may include, anynon-invasive hemodynamic sensor as described herein. The second sensor1015 may be, or may include, any non-invasive ECG or heart sound sensoras described herein.

In further related aspects, the apparatus 1000 may optionally include amodule for storing information, such as, for example, a memorydevice/module 1016. The computer readable medium or the memory module1016 may be operatively coupled to the other components of the apparatus1000 via the bus 1012 or the like. The memory module 1016 may be adaptedto store computer readable instructions and data for effecting theprocesses and behavior of the modules 1002-1007, and subcomponentsthereof, or the processor 1010, or the method 500 and one or more of theadditional operations 600-900 described in connection with the method500. The memory module 1016 may retain instructions for executingfunctions associated with the modules 1002-1007. While shown as beingexternal to the memory 1016, it is to be understood that the modules1002-1007 can exist within the memory 1016.

Referring to FIG. 11, an alternative method 1100 for approximation ofleft ventricular end diastolic pressure (LVEDP) using non-invasivesensors coupled to a computing apparatus, may include operations asdiagrammed in the Figures and/or described below. The method 1100 mayinclude, at 1110, receiving, by at least one processor of the computingapparatus, hemodynamic waveform data from a non-invasive sensor coupledto a patient and at least one of electrocardiogram (ECG) data or heartsound waveform data from a second non-invasive sensor coupled to thepatient. The method 1100 may further include at 1120 synchronizing, bythe at least one processor, the hemodynamic waveform data and the atleast one of electrocardiogram (ECG) data or heart sound waveform data.The method 1100 may further include at 1130 calculating, by the at leastone processor, an LVEDP based on time features and waveform features ofthe hemodynamic waveform data and the at least one of electrocardiogram(ECG) data or heart sound waveform data. As used herein, “time features”refer to features characterized by a time point or time period, forexample a time at which a waveform feature is marked, e.g., at abeginning, end, duration or middle. For example, an initiation time of adicrotic notch or a PEP are time features. Also as used herein,“waveform features” are functions of a waveform, for example, aderivative, intrinsic frequencies, and other characteristics of thewaveform in its characteristic space (e.g., time-pressure,time-displacement, time-amplitude, etc.).

Referring to FIGS. 12A-B and 6 the method 1100 may include any one ormore additional operations 1200, 600 as described above and belowherein. Each of these additional operations is not necessarily performedin every embodiment of the method, and the presence of any one of theoperations does not necessarily require that any other of theseadditional operations also be performed.

In an aspect, the method 1100 may further include at 1210, encoding theLVEDP as digital data for at least one of storage, transmission, orhuman-comprehensible output. At 1220, the method 1100 may furtherinclude determining, by the at least one processor, at least one of apre-ejection period (PEP) or an isovolumic contraction time (ICT), basedon simultaneous portions of the hemodynamic waveform data and at leastone of the ECG data or the heart sound waveform data. At 1230, themethod 1100 may further include, by the at least one processor,calculating a contractility feature based on the hemodynamic waveformdata. In an aspect, at 1240, the contractility feature may be, or mayinclude, at least one of a derivative of the hemodynamic waveform dataor intrinsic frequencies. At 1250, the method 1100 may further include,by the at least one processor, calculating the LVEDP as a function ofthe contractility feature, at least one of the PEP and the ICT, andoptionally a cuff blood pressure (DBP).

Referring to FIG. 12B, the method 1100 may further include at 1260,calculating the time features and waveform features of the hemodynamicwaveform data (HWD) and the at least one of electrocardiogram (ECG) dataor heart sound waveform (HSW) data based on at least one of: carotidpressure waveform, aortic wall waveform, carotid vessel wall waveform,radial pressure waveform, radial vessel wall waveform, brachial pressurewaveform, brachial vessel wall waveform, femoral pressure waveform,femoral vessel wall waveform, or pulseOx waveform. In an aspect, themethod 1100 may further include, at 1270, calculating the time featuresand waveform features of the hemodynamic waveform data and the at leastone of electrocardiogram (ECG) data or heart sound waveform data basedon or supplemented with at least one of: calculating a surrogate fromnon-invasively measured ejection fraction (EF) and fractional shortening(FS). In another aspect, at 1280 the method 1100 may further includecalculating the time features and waveform features of the hemodynamicwaveform data and the at least one of electrocardiogram (ECG) data orheart sound waveform data based on or supplemented with at least one ofa flow or velocity waveform.

Referring back to FIG. 6, in an aspect the hemodynamic waveform data isfrom heart sounds, and the method 1100 may further include, at 610collecting the waveform data from the heart sounds. In addition, themethod 1100 may further include, at 620, calculating of the LVEDP forvalvular diseases based on the waveform data collected from the heartsounds. In another aspect, at 630, the method 1100 may further includemeasuring the contractility feature by an imaging modality including atleast one cardiac magnetic resonance imaging or echocardiogram, in lieuof, or in addition to, deriving the contractility feature from waveformdata. Other aspects of the method 1100 may be as described herein abovegenerally, or in connection with the related method 500.

In accordance with the foregoing, FIG. 13 is a conceptual block diagramillustrating components of an apparatus or system 1300 for approximationof left ventricular end diastolic pressure (LVEDP) as described herein,according to an alternative embodiment. As depicted, the apparatus orsystem 1300 may include functional blocks that can represent functionsimplemented by a processor, software, or combination thereof (e.g.,firmware).

As illustrated in FIG. 13, the apparatus or system 1300 may comprise anelectrical component 1302 for receiving hemodynamic waveform data from anon-invasive sensor coupled to a patient and at least one ofelectrocardiogram (ECG) data or heart sound waveform data from a secondnon-invasive sensor coupled to the patient. The component 1302 may be,or may include, a means for said receiving. Said means may include theprocessor 1310 coupled to the memory 1316, to the first sensor 1314comprising a non-invasive hemodynamic sensor as described herein and tothe second sensor 1315 comprising an ECG sensor, the processor executingan algorithm based on program instructions stored in the memory. Suchalgorithm may include a sequence of more detailed operations, forexample, initiating communication sessions with the first sensor 1314and sensor 1315, correlating waveform from the sensors 1314, 1315 withrespect to a time datum, and encoding one or more characteristicfeatures of a received waveform from the sensors 1314, 1315 during thesession in a computer memory using a numeric scheme.

The apparatus or system 1300 may further comprise an electricalcomponent 1304 for synchronizing the hemodynamic waveform data and theat least one of electrocardiogram (ECG) data or heart sound waveformdata. The component 1304 may be, or may include, a means for saidsynchronizing. Said means may include the processor 1310 coupled to thememory 1316, and to the second sensor 1315 comprising an ECG or heartsound sensor, the processor executing an algorithm based on programinstructions stored in the memory. Such algorithm may include a sequenceof more detailed operations, for example, receiving separate waveformsfrom the sensors 1314, 1315 contemporaneously, determining a timedifference (e.g., signal lag) caused by any one or more ofcommunication, processing, or hemodynamical factors, if any, and if atime difference is determined, applying a correction factor tocompensate for the difference. One compensated, or if no time differenceis determined, the algorithm may include marking each waveform relativeto a common time datum.

The apparatus or system 1300 may further comprise an electricalcomponent 1306 for calculating an LVEDP based on time features andwaveform features of the hemodynamic waveform data and the at least oneof electrocardiogram (ECG) data or heart sound waveform data. Thecomponent 1306 may be, or may include, a means for said calculating.Said means may include the processor 1310 coupled to the memory 1316,the processor executing an algorithm based on program instructionsstored in the memory. Such algorithm may include a sequence of moredetailed operations, for example, executing operations for calculationof one or more of Equations 2.0-6.0 or 2.1-9.1 herein above.

The apparatus 1300 may optionally include a processor module 1310 havingat least one processor, in the case of the apparatus 1300 configured asa data processor. The processor 1310, in such case, may be in operativecommunication with the modules 1302-1306 via a bus 1312 or othercommunication coupling, for example, a network. The processor 1310 mayinitiate and schedule the processes or functions performed by electricalcomponents 1302-1306.

In related aspects, the apparatus 1300 may include a network interfacemodule (not shown) operable for communicating with a storage device overa computer network. The first sensor 1314 may be, or may include, anynon-invasive hemodynamic sensor as described herein. The second sensor1315 may be, or may include, any non-invasive ECG or heart sound sensoras described herein.

In further related aspects, the apparatus 1300 may optionally include amodule for storing information, such as, for example, a memorydevice/module 1316. The computer readable medium or the memory module1316 may be operatively coupled to the other components of the apparatus1300 via the bus 1312 or the like. The memory module 1316 may be adaptedto store computer readable instructions and data for effecting theprocesses and behavior of the modules 1302-1306, and subcomponentsthereof, or the processor 1310, or the method 1100 and one or more ofthe additional operations 1200, 600 described in connection with themethod 1100. The memory module 1316 may retain instructions forexecuting functions associated with the modules 1302-1306. While shownas being external to the memory 1316, it is to be understood that themodules 1302-1306 can exist within the memory 1316.

Those of skill would further appreciate that the various illustrativelogical blocks, modules, circuits, and algorithm steps described inconnection with the aspects disclosed herein may be implemented aselectronic hardware, computer software, or combinations of both. Toclearly illustrate this interchangeability of hardware and software,various illustrative components, blocks, modules, circuits, and stepshave been described above generally in terms of their functionality.Whether such functionality is implemented as hardware or softwaredepends upon the particular application and design constraints imposedon the overall system. Skilled artisans may implement the describedfunctionality in varying ways for each particular application, but suchimplementation decisions should not be interpreted as causing adeparture from the scope of the present disclosure.

RESULTS: Preliminary results for calculation of LVEDP are based onpreviously published data. Since pressure waveforms and as a result ω₁and ω₂ were not available for the data, EF was used as a surrogate of ω₁and ω₂:

$\begin{matrix}{{EF} = {{Y_{1}\left( {\omega_{1},\omega_{2},T_{o}} \right)}\overset{yields}{\rightarrow}\left\{ \begin{matrix}{\omega_{1} = {X_{1}\left( {{EF},T_{o}} \right)}} \\{\omega_{2} = {X_{2}\left( {{EF},T_{o}} \right)}}\end{matrix} \right.}} & (10)\end{matrix}$

This simply means that

LVEDP=k ₁(X ₁(EF,T _(o)),PEP)={acute over (k)} ₁(EF,T _(o) PEP)  (11)

Therefore, existence of {acute over (k)}₁ from the preliminary data willensures the existence of X₁ (or X₂).

Since ω₁ √{square root over (T_(o))} is well correlated to EF based onour unpublished data, it can be replaced in Equation 3.1 that gives:

$\begin{matrix}{{LVEDP} = {{c_{1}{AoDP}} + {c_{2}\frac{{EF} \times {PEP}}{\sqrt{T_{o}}}}}} & (12)\end{matrix}$

Results excluding valvular disease and Arrhythmia: Graph 1400 of FIG. 14shows approximation of LVEDP from Equation 8.1 using AoDP, EF, PEP, andLV ejection time (T0). In order to test the hypothesis, 24 data points(excluding valvular disease and Arrhythmia) published by Garrard et al(Garrard C L, Weissler A M, Dodge HT (1970) The Relationship ofAlterations in Systolic Time Intervals to Ejection Fraction in Patientswith Cardiac Disease. Circulation 42: 455-462) was used to compute LVEDPusing Equation 8.1. A multiple linear regression with two variable (tworegressor) was applied to computec₀,c₁, and c₂ and the intercept. Theresult shows R=82.5 (R-adjusted=80.5), Limit of agreement (LoA)=+−11.4,and root mean square error (RMSE)=5.68 mmHg.

As shown in FIG. 14, the model does not produce any false negative(LVEDPcalc<13 while LVEDP>13), and it only have one false positive(LVEDPcalc>13 while LVEDP<13).

Since EF is afterload dependent, LVEDP can also be approximated withoutAoDP as shown in Equation (9.6):

$\begin{matrix}{{LVEDP} \propto \frac{{EF} \times {PEP}}{\sqrt{T_{o}}}} & (9.6)\end{matrix}$

With the same data set of Garrard et al, Equation 9.6 by itself shows81.5 percent correlation with LVEDP.

Graph 1500 of FIG. 15 shows approximation of LVEDP from linearregression using EF, PEP, and ejection time (T0). Data was trained on 20subjects and applied of 14 subjects presented here. In another data setthat includes data of Garrard et al plus 10 subject data from Lewis etal (Lewis B S, Armstrong T G, Everson R C, Gotsman M S (1973) Predictivevalue of the systolic time intervals in primary myocardial disease.Chest 64: 431-438) that sums up to 34 data points, a linear multipleregression model (EF, PEP, and LVET as parameters) was trained on 20data points and test on the other 14 subjects. The result shows R=0.84,LoA=+10−13.5 and RMSE=6.1 mmHg

Graph 1600 of FIG. 16 shows approximation of LVEDP from multipleregression (interaction model) using EF, PEP, and ejection time (T0).Data includes subjects with valvular disease and arrhythmia.

Results including valvular disease and Arrhythmia: 93 data points (alldata points) published by Garrard et al were used on a quadraticmultiple regression model (parameters are PEP/LVET and EF that give 5regressors) to approximate LVEDP. The result shows R=0.71 and LoA=+−13.7

Using interactions multiple regression between PEP,LVET and EF for LVEDP(6 regressor) gives R=0.74, LoA=+−13.3 and RMSE=6.8 mmHg.

Graph 1700 of FIG. 17 shows correlation between LVEDP and Equation (9).Equation 9

$\left( \frac{{EF} \times {PEP}}{\sqrt{LVET}} \right)$

by itself shows 69 percent correlation with LVEDP, RMSE=7.4 mmHg.

GENERAL REMARKS: As used in this application, the terms “component”,“module”, “system”, and the like are intended to refer to acomputer-related entity, either hardware, a combination of hardware andsoftware, software, or software in execution. For example, a componentmay be, but is not limited to being, a process running on a processor, aprocessor, an object, an executable, a thread of execution, a program,and/or a computer or system of cooperating computers. By way ofillustration, both an application running on a server and the server canbe a component. One or more components may reside within a processand/or thread of execution and a component may be localized on onecomputer and/or distributed between two or more computers.

Various aspects are presented in terms of systems that may include anumber of components, modules, and the like. It is to be understood andappreciated that the various systems may include additional components,modules, etc. and/or may not include all the components, modules, etc.discussed in connection with the figures. A combination of theseapproaches may also be used. The various aspects disclosed herein can beperformed on electrical devices including devices that utilize touchscreen display technologies and/or mouse-and-keyboard type interfaces.Examples of such devices include computers (desktop and mobile), smartphones, personal digital assistants (PDAs), and other electronic devicesboth wired and wireless.

In addition, the various illustrative logical blocks, modules, andcircuits described in connection with the aspects disclosed herein maybe implemented or performed with a general purpose processor, a digitalsignal processor (DSP), an application specific integrated circuit(ASIC), a field programmable gate array (FPGA) or other programmablelogic device, discrete gate or transistor logic, discrete hardwarecomponents, or any combination thereof designed to perform the functionsdescribed herein. A general-purpose processor may be a microprocessor,but in the alternative, the processor may be any conventional processor,controller, microcontroller, or state machine. A processor may also beimplemented as a combination of computing devices, e.g., a combinationof a DSP and a microprocessor, a plurality of microprocessors, one ormore microprocessors in conjunction with a DSP core, or any other suchconfiguration.

Operational aspects disclosed herein may be embodied directly inhardware, in a software module executed by a processor, or in acombination of the two. A software module may reside in RAM memory,flash memory, ROM memory, EPROM memory, EEPROM memory, registers, harddisk, a removable disk, a CD-ROM, or any other form of storage mediumknown in the art. An exemplary storage medium is coupled to theprocessor such the processor can read information from, and writeinformation to, the storage medium. In the alternative, the storagemedium may be integral to the processor. The processor and the storagemedium may reside in an ASIC. The ASIC may reside in a user terminal. Inthe alternative, the processor and the storage medium may reside asdiscrete components in a user terminal.

Furthermore, the one or more versions may be implemented as a method,apparatus, or article of manufacture using standard programming and/orengineering techniques to produce software, firmware, hardware, or anycombination thereof to control a computer to implement the disclosedaspects. Non-transitory computer readable media can include but are notlimited to magnetic storage devices (e.g., hard disk, floppy disk,magnetic strips . . . ), optical disks (e.g., compact disk (CD), digitalversatile disk (DVD), BluRay™ . . . ), smart cards, solid-state devices(SSDs), and flash memory devices (e.g., card, stick). Of course, thoseskilled in the art will recognize many modifications may be made to thisconfiguration without departing from the scope of the disclosed aspects.

In view of the exemplary systems described supra, methodologies that maybe implemented in accordance with the disclosed subject matter have beendescribed with reference to several flow diagrams. While for purposes ofsimplicity of explanation, the methodologies are shown and described asa series of blocks, it is to be understood and appreciated that theclaimed subject matter is not limited by the order of the blocks, assome blocks may occur in different orders and/or concurrently with otherblocks from what is depicted and described herein. Moreover, not allillustrated blocks may be required to implement the methodologiesdescribed herein. Certain details are omitted from the drawings forillustrative simplicity, appearing only in the detailed description.Additionally, it should be further appreciated that the methodologiesdisclosed herein are capable of being stored on an article ofmanufacture to facilitate transporting and transferring suchmethodologies to computers.

The foregoing description is provided to enable any person skilled inthe art to make or use the present disclosure. Various modifications tothe disclosed aspects will be clear to those skilled in the art, and thegeneric principles defined herein may be applied to other embodimentswithout departing from the spirit or scope of the disclosure. Thus, thepresent disclosure is not intended to be limited to the embodimentsshown herein but is to be accorded the widest scope consistent with theprinciples and novel features disclosed herein.

1-24. (canceled)
 25. A method for approximation of left ventricular enddiastolic pressure (LVEDP) using non-invasive sensors coupled to acomputing apparatus, the method comprising: receiving, by at least oneprocessor of the computing apparatus, hemodynamic waveform data from anon-invasive sensor coupled to a patient and at least one ofelectrocardiogram (ECG) data or heart sound waveform data from a secondnon-invasive sensor coupled to the patient; synchronizing, by the atleast one processor, the hemodynamic waveform data and the at least oneof electrocardiogram (ECG) data or heart sound waveform data,calculating, by the at least one processor, an LVEDP based on timefeatures and waveform features of the hemodynamic waveform data and theat least one of electrocardiogram (ECG) data or heart sound waveformdata.
 26. The method of claim 25, further comprising encoding the LVEDPas digital data for at least one of storage, transmission, orhuman-comprehensible output.
 27. The method of claim 25, furthercomprising determining, by the at least one processor, at least one of apre-ejection period (PEP) or an isovolumic contraction time (ICT), basedon simultaneous portions of the hemodynamic waveform data and at leastone of the ECG data or the heart sound waveform data.
 28. The method ofclaim 27, further comprising calculating, by the at least one processor,a contractility feature based on the hemodynamic waveform data.
 29. Themethod of claim 28, wherein the at least one processor calculates theLVEDP as a function of the contractility feature, at least one of thePEP and the ICT, and optionally a cuff blood pressure (DBP).
 30. Themethod of claim 28, wherein the contractility feature comprises at leastone of a derivative of the hemodynamic waveform data or intrinsicfrequencies.
 31. The method of claim 25, wherein the hemodynamicwaveform data is comprised of heart sounds, and further comprisingcollecting the waveform data from the heart sounds.
 32. The method ofclaim 31, further comprising correcting the calculating of the LVEDP forvalvular diseases based on the waveform data collected from the heartsounds.
 33. The method of claim 25, wherein calculating the timefeatures and waveform features of the hemodynamic waveform data and theat least one of electrocardiogram (ECG) data or heart sound waveformdata is based on at least one of: carotid pressure waveform, aortic wallwaveform, carotid vessel wall waveform, radial pressure waveform, radialvessel wall waveform, brachial pressure waveform, brachial vessel wallwaveform, femoral pressure waveform, femoral vessel wall waveform, orpulseOx waveform.
 34. The method of claim 25, wherein calculating thetime features and waveform features of the hemodynamic waveform data andthe at least one of electrocardiogram (ECG) data or heart sound waveformdata is based on or supplemented with at least one of: calculating asurrogate from non-invasively measured ejection fraction (EF) andfractional shortening (FS).
 35. The method of claim 25, whereincalculating the time features and waveform features of the hemodynamicwaveform data and the at least one of electrocardiogram (ECG) data orheart sound waveform data is based on or supplemented with at least oneof a flow or velocity waveform.
 36. An apparatus for approximation ofleft ventricular end diastolic pressure (LVEDP) comprising at least oneprocessor coupled to a memory, to a non-invasive hemodynamic waveformsensor, and to at least one of a non-invasive electrocardiogram (ECG)sensor or heart sound waveform sensor, wherein the memory holds programinstructions that when executed by the at least one processor cause theapparatus to perform: receiving hemodynamic waveform data from anon-invasive sensor coupled to a patient and at least one ofelectrocardiogram (ECG) data or heart sound waveform data from a secondnon-invasive sensor coupled to the patient; synchronizing, thehemodynamic waveform data and the at least one of electrocardiogram(ECG) data or heart sound waveform data, calculating an LVEDP based ontime features and waveform features of the hemodynamic waveform data andthe at least one of electrocardiogram (ECG) data or heart sound waveformdata.
 37. The apparatus of claim 33, wherein the memory holdsinstructions for encoding the LVEDP as digital data for at least one ofstorage, transmission, or human-comprehensible output.
 38. The apparatusof claim 33, wherein the memory holds instructions for determining, atleast one of a pre-ejection period (PEP) or an isovolumic contractiontime (ICT), based on simultaneous portions of the hemodynamic waveformdata and at least one of the ECG data or the heart sound waveform data.39. The apparatus of claim 35, wherein the memory holds instructions forcalculating a contractility feature based on the hemodynamic waveformdata.
 40. The apparatus of claim 36, wherein the memory holdsinstructions for calculating the LVEDP as a function of thecontractility feature, at least one of the PEP and the ICT, andoptionally a cuff blood pressure (DBP).
 41. The apparatus of claim 37,wherein the memory holds instructions for the calculating contractilityfeature comprising at least one of a derivative of the hemodynamicwaveform data or intrinsic frequencies.
 42. The apparatus of claim 33,wherein the memory holds instructions for collecting a heart sound. 43.The apparatus of claim 39, wherein the memory holds instructions forcorrecting the calculating of the LVEDP for valvular diseases based onthe heart sound.